Granular computing in decision approximation: an application of rough mereology
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cham [u.a.]
Springer
2015
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Schriftenreihe: | Intelligent systems reference library
77 |
Schlagworte: | |
Online-Zugang: | BHS01 BTU01 FAB01 FAW01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract |
Beschreibung: | 1 Online-Ressource (XV, 452 p. 230 illus) |
ISBN: | 9783319128801 |
DOI: | 10.1007/978-3-319-12880-1 |
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Datensatz im Suchindex
DE-BY-FWS_katkey | 559568 |
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adam_text | GRANULAR COMPUTING IN DECISION APPROXIMATION
/ POLKOWSKI, LECH
: 2015
TABLE OF CONTENTS / INHALTSVERZEICHNIS
SIMILARITY AND GRANULATION
MEREOLOGY AND ROUGH MEREOLOGY. ROUGH MEREOLOGICAL GRANULATION
LEARNING DATA CLASSIFICATION. CLASSIFIERS IN GENERAL AND IN DECISION
SYSTEMS
METHODOLOGIES FOR GRANULAR REFLECTIONS
COVERING STRATEGIES
LAYERED GRANULATION
NAIVE BAYES CLASSIFIER ON GRANULAR REFLECTIONS
THE CASE OF CONCEPT-DEPENDENT GRANULATION
GRANULAR COMPUTING IN THE PROBLEM OF MISSING VALUES
GRANULAR CLASSIFIERS BASED ON WEAK ROUGH INCLUSIONS
EFFECTS OF GRANULATION ON ENTROPY AND NOISE IN DATA. - CONCLUSIONS
APPENDIX. DATA CHARACTERISTICS BEARING ON CLASSIFICATION
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
GRANULAR COMPUTING IN DECISION APPROXIMATION
/ POLKOWSKI, LECH
: 2015
ABSTRACT / INHALTSTEXT
THIS BOOK PRESENTS A STUDY IN KNOWLEDGE DISCOVERY IN DATA WITH KNOWLEDGE
UNDERSTOOD AS A SET OF RELATIONS AMONG OBJECTS AND THEIR PROPERTIES.
RELATIONS IN THIS CASE ARE IMPLICATIVE DECISION RULES AND THE PARADIGM
IN WHICH THEY ARE INDUCED IS THAT OF COMPUTING WITH GRANULES DEFINED BY
ROUGH INCLUSIONS, THE LATTER INTRODUCED AND STUDIED WITHIN ROUGH
MEREOLOGY, THE FUZZIFIED VERSION OF MEREOLOGY. IN THIS BOOK BASIC
CLASSES OF ROUGH INCLUSIONS ARE DEFINED AND BASED ON THEM METHODS FOR
INDUCING GRANULAR STRUCTURES FROM DATA ARE HIGHLIGHTED. THE RESULTING
GRANULAR STRUCTURES ARE SUBJECTED TO CLASSIFYING ALGORITHMS, NOTABLY
K—NEAREST NEIGHBORS AND BAYESIAN CLASSIFIERS. EXPERIMENTAL RESULTS
ARE GIVEN IN DETAIL BOTH IN TABULAR AND VISUALIZED FORM FOR FOURTEEN
DATA SETS FROM UCI DATA REPOSITORY. A STRIKING FEATURE OF GRANULAR
CLASSIFIERS OBTAINED BY THIS APPROACH IS THAT PRESERVING THE ACCURACY OF
THEM ON ORIGINAL DATA, THEY REDUCE SUBSTANTIALLY THE SIZE OF THE
GRANULATED DATA SET AS WELL AS THE SET OF GRANULAR DECISION RULES. THIS
FEATURE MAKES THE PRESENTED APPROACH ATTRACTIVE IN CASES WHERE A SMALL
NUMBER OF RULES PROVIDING A HIGH CLASSIFICATION ACCURACY IS DESIRABLE.
AS BASIC ALGORITHMS USED THROUGHOUT THE TEXT ARE EXPLAINED AND
ILLUSTRATED WITH HAND EXAMPLES, THE BOOK MAY ALSO SERVE AS A TEXTBOOK
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
any_adam_object | 1 |
author | Polkowski, Lech |
author_facet | Polkowski, Lech |
author_role | aut |
author_sort | Polkowski, Lech |
author_variant | l p lp |
building | Verbundindex |
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collection | ZDB-2-ENG |
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dewey-full | 006.3 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.3 |
dewey-search | 006.3 |
dewey-sort | 16.3 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
doi_str_mv | 10.1007/978-3-319-12880-1 |
format | Electronic eBook |
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indexdate | 2024-08-01T12:06:08Z |
institution | BVB |
isbn | 9783319128801 |
language | English |
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owner | DE-1046 DE-1043 DE-B768 DE-Aug4 DE-898 DE-BY-UBR DE-573 DE-859 DE-863 DE-BY-FWS DE-634 DE-92 DE-862 DE-BY-FWS DE-861 DE-706 |
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physical | 1 Online-Ressource (XV, 452 p. 230 illus) |
psigel | ZDB-2-ENG ZDB-2-ENG_2015 |
publishDate | 2015 |
publishDateSearch | 2015 |
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publisher | Springer |
record_format | marc |
series | Intelligent systems reference library |
series2 | Intelligent systems reference library |
spellingShingle | Polkowski, Lech Granular computing in decision approximation an application of rough mereology Intelligent systems reference library Engineering Artificial intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz |
title | Granular computing in decision approximation an application of rough mereology |
title_auth | Granular computing in decision approximation an application of rough mereology |
title_exact_search | Granular computing in decision approximation an application of rough mereology |
title_full | Granular computing in decision approximation an application of rough mereology Lech Polkowski ; Piotr Artiemjew |
title_fullStr | Granular computing in decision approximation an application of rough mereology Lech Polkowski ; Piotr Artiemjew |
title_full_unstemmed | Granular computing in decision approximation an application of rough mereology Lech Polkowski ; Piotr Artiemjew |
title_short | Granular computing in decision approximation |
title_sort | granular computing in decision approximation an application of rough mereology |
title_sub | an application of rough mereology |
topic | Engineering Artificial intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz |
topic_facet | Engineering Artificial intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz |
url | https://doi.org/10.1007/978-3-319-12880-1 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027978332&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027978332&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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